IDEAS home Printed from https://ideas.repec.org/p/gla/glaewp/2021_17.html
   My bibliography  Save this paper

Health Dynamics and Heterogeneous Life Expectancies

Author

Listed:
  • Richard Foltyn
  • Jonna Olsson

Abstract

Using biennial data from the Health and Retirement Study, we estimate age-dependent health dynamics and survival probabilities at annual frequency conditional on race, sex, and health. The health gradient in life expectancy is steep and persists after controlling for socioeconomic status. Moreover, even conditional on health and socioeconomic status, the racial gap in life expectancy remains large. Simulations show that this gap affects savings rates but does not play a major role in explaining the racial wealth gap. However, differences in mortality imply that black individuals on average can expect to receive 15% less in Social Security benefits in present value terms.

Suggested Citation

  • Richard Foltyn & Jonna Olsson, 2021. "Health Dynamics and Heterogeneous Life Expectancies," Working Papers 2021_17, Business School - Economics, University of Glasgow.
    • Handle: RePEc:gla:glaewp:2021_17
    as

    Download full text from publisher

    File URL: https://www.gla.ac.uk/media/Media_811161_smxx.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mariacristina De Nardi & Eric French & John B. Jones, 2010. "Why Do the Elderly Save? The Role of Medical Expenses," Journal of Political Economy, University of Chicago Press, vol. 118(1), pages 39-75, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aydilek, Asiye, 2016. "The allocation of time and puzzling profiles of the elderly," Economic Modelling, Elsevier, vol. 53(C), pages 515-526.
    2. Goda, Gopi Shah & Manchester, Colleen Flaherty & Sojourner, Aaron J., 2014. "What will my account really be worth? Experimental evidence on how retirement income projections affect saving," Journal of Public Economics, Elsevier, vol. 119(C), pages 80-92.
    3. Goda, Gopi Shah & Ramnath, Shanthi & Shoven, John B. & Slavov, Sita Nataraj, 2018. "The financial feasibility of delaying Social Security: evidence from administrative tax data," Journal of Pension Economics and Finance, Cambridge University Press, vol. 17(4), pages 419-436, October.
    4. Patrick Richard & Regine Walker & Pierre Alexandre, 2018. "The burden of out of pocket costs and medical debt faced by households with chronic health conditions in the United States," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-13, June.
    5. Ni, Xinwen, 2019. "Voting for Health Insurance Policy: the U.S. versus Europe," IRTG 1792 Discussion Papers 2019-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Chen, Li-Shiun & Wang, Ping & Yao, Yao, 2018. "Power of personalized smoking cessation: A unified lifecycle framework for policy evaluation," Working Paper Series 20333, Victoria University of Wellington, School of Economics and Finance.
    7. Svetlana Pashchenko & Ponpoje (Poe) Porapakkarm & Mariacristina De Nardi, 2017. "The Lifetime Costs of Bad Health," 2017 Meeting Papers 533, Society for Economic Dynamics.
    8. Kuhn, Michael & Frankovic, Ivan & Wrzaczek, Stefan, 2017. "Medical Progress, Demand for Health Care, and Economic Performance," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168249, Verein für Socialpolitik / German Economic Association.
    9. James Poterba & Steven Venti & David Wise, 2011. "The Composition and Drawdown of Wealth in Retirement," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 95-118, Fall.
    10. Asako Ohinata & Matteo Picchio, 2020. "Financial support for long-term elderly care and household saving behaviour," Oxford Economic Papers, Oxford University Press, vol. 72(1), pages 247-268.
    11. Mariacristina De Nardi & Eric French & John Bailey Jones, 2016. "Medicaid Insurance in Old Age," American Economic Review, American Economic Association, vol. 106(11), pages 3480-3520, November.
    12. Poterba, James M. & Venti, Steven F. & Wise, David A., 2017. "The asset cost of poor health," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 172-184.
    13. FUKAI Taiyo & ICHIMURA Hidehiko & KANAZAWA Kyogo, 2018. "Quantifying Health Shocks over the Life Cycle," Discussion papers 18014, Research Institute of Economy, Trade and Industry (RIETI).
    14. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    15. Hero Ashman & Seth Neumuller, 2020. "Can Income Differences Explain the Racial Wealth Gap: A Quantitative Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 220-239, January.
    16. Zsofia Barany & Nicolas Coeurdacier & Stéphane Guibaud, 2015. "Fertility, Longevity and International Capital Flows," Sciences Po publications info:hdl:2441/5402sfihji9, Sciences Po.
    17. Kindermann, Fabian & Mayr, Lukas & Sachs, Dominik, 2020. "Inheritance taxation and wealth effects on the labor supply of heirs," Journal of Public Economics, Elsevier, vol. 191(C).
    18. Joachim Inkmann & Alexander Michaelides, 2012. "Can the Life Insurance Market Provide Evidence for a Bequest Motive?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 79(3), pages 671-695, September.
    19. d’Albis, Hippolyte & El Mekkaoui, Najat & Legendre, Bérangère, 2023. "Health accidents and wealth decline in old age," Social Science & Medicine, Elsevier, vol. 332(C).
    20. Huang, H. & Milevsky, M.A. & Salisbury, T.S., 2017. "Retirement spending and biological age," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 58-76.

    More about this item

    Keywords

    Life expectancy; health dynamics; racial life expectancy gap;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gla:glaewp:2021_17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Business School Research Team (email available below). General contact details of provider: https://edirc.repec.org/data/dpglauk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.